Systems and methods for removing non-conforming web text

A system comprising:

• one or more processors;
• and
• one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations comprising:
• determining web text sentiment scores for web texts;
• creating a ranked list of one or more match words in the web texts;
• periodically scoring, for a specified period of time, the one or more match words in the ranked list of the one or more match words based on the web text sentiment scores and mention weights associated with the one or more match words for the specified period of time;
• labeling, using a generative model, the one or more match words to create labeled training data;
• training, using the labeled training data, a word-based classifier to identify non-conforming web text submitted for display on a website, wherein the training of the word-based classifier comprises using embedded images to train an image-based classifier to classify an image into at least one classification by applying a natural language processing algorithm to a vector representation of the image, wherein the at least one classification comprises a non-conforming image;
• receiving first web text for display on the website;
• using the word-based classifier, as trained, to identify the first web text as non-conforming web text when the word-based classifier determines at least a classifier score for the first web text to exceed a predetermined threshold;
• and
• automatically not displaying the first web text on the website when at least the classifier score exceeds the predetermined threshold.